Effect of thinning intensity on the carbon sequestration of natural mixed coniferous and broadleaf forests in Xiaoxing'an Mountains, China

To study the effect of thinning intensity on the carbon sequestration by natural mixed coniferous and broad-leaf forests in Xiaoxing’an Mountains,China,we established six 100 m×100 m experimental plots in Dongfanghong For-est that varied in thinning intensity:plot A(10%),B(15%),C(20%),D(25%),E(30%),F(35%),and the control sample area(0%).A principal component analysis was performed using 50 different variables,including species diversity,soil fertility,litter characteristics,canopy structure param-eters,and seedling regeneration parameters.The effects of thinning intensity on carbon sequestration were strongest in plot E(0.75),followed by D(0.63),F(0.50),C(0.48),B(0.22),A(0.11),and the control(0.06).The composite score of plot E was the highest,indicating that the carbon sequestration effect was strongest at a thinning intensity of 30%.These findings provide useful insights that could aid the management of natural mixed coniferous and broadleaf forests in Xiaoxing’an Mountains,China.This information has implications for future studies of these forests,and the methods used could aid future ecological assessments of the natural forests in Xiaoxing’an Mountains,China.

Eff ects of thinning on ecosystem carbon storage and tree-shrub-herb diversity of a low-quality secondary forest in NE China

Thinning is a widely used forest management tool but systematic research has not been carried out to verify its eff ects on carbon storage and plant diversity at the ecosystem level.In this study,the eff ect of thinning was assessed across seven thinning intensities(0,10,15,20,25,30 and 35%)in a low-quality secondary forest in NE China over a ten-year period.Thinning aff ected the carbon storage of trees,and shrub,herb,and soil layers(P<0.05).It fi rst increased and then decreased as thinning intensity increased,reaching its maximum at 30%thinning.Carbon storage of the soil accounted for more than 64%of the total carbon stored in the ecosystem.It was highest in the upper 20-cm soil layer.Thinning increased tree species diversity while decreasing shrub and herb diversities(P<0.05).Redundancy analysis and a correlation heat map showed that carbon storage of tree and shrub layers was positively correlated with tree diversity but negatively with herb diversity,indicating that the increase in tree diversity increased the carbon storage of natural forest ecosystems.Although thinning decreased shrub and herb diversities,it increased the carbon storage of the overall ecosystem and tree species diversity of secondary forest.Maximum carbon storage and the highest tree diversity were observed at a thinning intensity of 30%.This study provides evidence for the ecological management of natural and secondary forests and improvement of ecosystem carbon sinks and biodiversity.

Thinning intensity aff ects carbon sequestration and release in seasonal freeze–thaw areas

To explore how to respond to seasonal freeze–thaw cycles on forest ecosystems in the context of climate change through thinning,we assessed the potential impact of thinning intensity on carbon cycle dynamics.By varying the number of temperature cycles,the eff ects of various thinning intensities in four seasons.The rate of mass,litter organic carbon,and soil organic carbon(SOC)loss in response to temperature variations was examined in two degrees of decomposition.The unfrozen season had the highest decomposition rate of litter,followed by the frozen season.Semi-decomposed litter had a higher decomposition rate than undecomposed litter.The decomposition rate of litter was the highest when the thinning intensity was 10%,while the litter and SOC were low.Forest litter had a good carbon sequestration impact in the unfrozen and freeze–thaw seasons,while the converse was confi rmed in the frozen and thaw seasons.The best carbon sequestration impact was identifi ed in litter,and soil layers under a 20–25%thinning intensity,and the infl uence of undecomposed litter on SOC was more noticeable than that of semi-decomposed litter.Both litter and soil can store carbon:however,carbon is transported from undecomposed litter to semi-decomposed litter and to the soil over time.In summary,the best thinning intensity being 20–25%.

A novel model to evaluate spatial structure in thinned conifer-broadleaved mixed natural forests

In order to ensure the effective analysis and reconstruction of forests,it is key to ensure the quantitative description of their spatial structure.In this paper,a distance model for the optimal stand spatial structure based on weighted Voronoi diagrams is proposed.In particular,we provide a novel methodological model for the comprehensive evaluation of the spatial structure of forest stands in natural mixed conifer-broadleaved forests and the formulation of management decision plans.The applicability of the rank evaluation and the optimal solution distance model are compared and assessed for different standard sample plots of natural mixed conifer-broadleaved forests.The effect of crown width on the spatial structure unit of the trees is observed to be higher than that of the diameter at breast height.Moreover,the influence of crown length is greater than that of tree height.There are nine possible spatial structure units determined by the weighted Voronoi diagram for the number of neighboring trees in the central tree,with an average intersection of neighboring crowns reaching 80%.The rank rating of natural forest sample plots is correlated with the optimal solution distance model,and their results are generally consistent for natural forests.However,the rank rating is not able to provide a quantitative assessment.The optimal solution distance model is observed to be more comprehensive than traditional methods for the evaluation of the spatial structure of forest stands.It can effectively reflect the trends in realistic stand spatial structure factors close to or far from the ideal structure point,and accurately assesses the forest spatial structure.The proposed optimal solution distance model improves the integrated evaluation of the spatial structure of forest stands and provides solid theoretical and technical support for sustainable forest management.

A survey on ensemble learning

Despite significant successes achieved in knowledge discovery,traditional machine learning methods may fail to obtain satisfactory performances when dealing with complex data,such as imbalanced,high-dimensional,noisy data,etc.The reason behind is that it is difficult for these methods to capture multiple characteristics and underlying structure of data.In this context,it becomes an important topic in the data mining field that how to effectively construct an efficient knowledge discovery and mining model.Ensemble learning,as one research hot spot,aims to integrate data fusion,data modeling,and data mining into a unified framework.Specifically,ensemble learning firstly extracts a set of features with a variety of transformations.Based on these learned features,multiple learning algorithms are utilized to produce weak predictive results.Finally,ensemble learning fuses the informative knowledge from the above results obtained to achieve knowledge discovery and better predictive performance via voting schemes in an adaptive way.In this paper,we review the research progress of the mainstream approaches of ensemble learning and classify them based on different characteristics.In addition,we present challenges and possible research directions for each mainstream approach of ensemble learning,and we also give an extra introduction for the combination of ensemble learning with other machine learning hot spots such as deep learning,reinforcement learning,etc.